Crop yield, soil properties, and erosion are strongly related to terrain attributes. The objectives of our study were to examine the relationship between six years of corn (Zea mays L.) yield data and relative elevation, slope, and curvature, and to develop a linear regression model to describe the spatial patterns of corn yield for a 16 ha field in central Iowa, USA. Corn grain yield was measured in six crop years, and relative elevation was measured using a kinematic global positioning system. Slope and curvature were then determined using digital terrain analysis. Our data showed that in the four years with less than normal growing season precipitation, corn yield was negatively correlated with relative elevation, slope, and curvature. In the two years with greater than normal precipitation, yield was positively correlated with relative elevation and slope. A multiple linear regression model based on relative elevation, slope, and curvature was developed that predicted 78% of the spatial variability of the average yield of the transect plots for the four dry years. This model also adequately identified the spatial patterns within the entire field for yield monitor data from 1997, which was one of the dry years. The relationship between terrain attributes and corn yield spatial patterns may provide opportunities for implementing site-specific management.
Precision Agriculture – Springer Journals
Published: Oct 3, 2004
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